This application addresses NHLBI Participation in NIH Research and Research Infrastructure "Grand Opportunities" (RC2) (RFA-OD-09-004);NHLBI RC2 topic area "Novel Methods of Measuring Health Disparities." The broad goal of this project is to design a population-based surveillance system that integrates multiple data sources to track disparities in chronic diseases at the local level. This system will capture the complete spectrum of relevant information from socio-economic context and health risk factors to disease incidence and the consequent cascade of hospitalizations, outpatient visits, and use of and adherence to interventions. The project will demonstrate the costs and feasibility of this system in King County, Washington. By demonstrating in this two-year project, the feasibility of such an integrated cost-effective system, it could be subsequently deployed in a number of sites across the United States. Together these sites would provide important detail on chronic disease disparities for race/ethnicity groups in different parts of the country. The integrated multi-source data system will need certain key attributes. First, it should leverage existing data systems including medical record discharge systems, vital registration data, census data, reportable conditions, payer data systems and Medicare files. Second, it should supplement these sources with additional cost-effective data collection including household surveys and chart extraction. Third, the quality and utility of the information should be maximized through record linkage across data platforms. Finally, the methods and strategies used in King County should be applicable in diverse communities across the US. PUBLIC HEALTH RELEVANCE: Tracking and analyzing the disparities for race/ethnicity groups across counties or local communities requires detailed measurements for at least four critical domains: health outcomes, health risk factors, health services, and the socio-economic context. The broad goal of this project is to design a population-based surveillance system that integrates multiple -data sources to track disparities in chronic diseases at the local level. This will allow more targeted allocation of limited resources and more detailed, specific information that can be used by policy makers to design appropriate interventions.